Structure

MLDecisionTreeClassifier.ModelParameters

Parameters that affect the process of training a model.

Declaration

struct MLDecisionTreeClassifier.ModelParameters

Topics

Accessing Parameters

var validationData: MLDataTable?

The data used for the validation set to inform the model training process.

Deprecated
var maxDepth: Int

The maximum depth of the tree. Must be greater than 0.

var minLossReduction: Double

The minimum amount that the loss needs to be reduced to create a new split.

var minChildWeight: Double

The minimum weight of each leaf node.

var randomSeed: Int

The seed value for random operations during tree building process.

Describing Parameters

var description: String

A text representation of the model parameters for a decision tree classifier.

var debugDescription: String

A text representation of the model parameters for a decision tree classifier that’s suitable for output during debugging.

var playgroundDescription: Any

A description of the model parameters for a decision tree classifier shown in a playground.

See Also

Creating and Training a Model

init(trainingData: MLDataTable, targetColumn: String, featureColumns: [String]?, parameters: MLDecisionTreeClassifier.ModelParameters)

Creates a Decision Tree Classifier from the feature columns in the training data to predict the categories in the target column.

Beta Software

This documentation contains preliminary information about an API or technology in development. This information is subject to change, and software implemented according to this documentation should be tested with final operating system software.

Learn more about using Apple's beta software